Economical and efficient big data sharing with i-Cloud

Banditwattanawong, Thepparit; Masdisornchote, Masawee; Uthayopas, Putchong

doi:10.1109/bigcomp.2014.6741417

Cited by 7 publications

(6 citation statements)

References 9 publications

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“…There is also the question of data repository longevity -who funds the repositories for decades into the future? Currently, some researchers now have to pay data egress charges for downloading data from cloud providers [88][89][90]. This method presumably saves the data producers money in terms of storing large datasets publicly, but the cost is somewhat now presented to the consumer.…”

Section: Discussionmentioning

confidence: 99%

Knowledge and attitudes among life scientists towards reproducibility within journal articles: a research survey

Samota

Davey

2019

Preprint

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We constructed a survey to understand how authors and scientists view the issues around reproducibility, and how solutions such as interactive figures could enable the reproducibility of experiments from within a research article. This manuscript reports the results of this survey on the views of 251 researchers, including authors who have published in eLIFE Sciences, and those who work at the Norwich Biosciences Institutes (NBI). The survey also outlines to what extent researchers are occupied with reproducing experiments themselves and what are their desirable features of an interactive figure. Respondents considered various features for an interactive figure within a research article that would allow for them to better understand and reproduce in situ the experiment presented in the figure. Respondents said that the most important element that would enable the better reproducibility of published research would be that authors describe methods and analyses in detail.The respondents believe that having an interactive figures in published papers is a beneficial element.Whilst interactive figures are potential solutions for demonstrating technical reproducibility, we find that there are equally pressing cultural demands on researchers that need to be addressed to achieve greater success in reproducibility in the life sciences .

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Section: Discussionmentioning

confidence: 99%

Knowledge and attitudes among life scientists towards reproducibility within journal articles: a research survey

Samota

Davey

2019

Preprint

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“…However, such work has been studied totally in uniform cost environments. The working behaviors of i-Cloud have been further revealed in [64], using a mixed pair of small uniform-cost training data sets collected from different user communities, and in [65] having i-Cloud learned a uniform-cost data set and operated against nonuniform costs.…”

Section: Object Cacheabilitymentioning

confidence: 99%

Multi-provider cloud computing network infrastructure optimization

Banditwattanawong

Masdisornchote

Uthayopas

2016

Future Generation Computer Systems

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h i g h l i g h t s• Byte-hit rate and hit rate could be optimal simultaneously in a nonuniform cost model. • i-Cloud outperformed popular LRU, GDSF and LFUDA schemes in a nonuniform cost environment.• i-Cloud's performances were stable and close to those of infinite cache size. • Window size had small performance effect when relative cache sizes were big.• Accounting data-out charge rates improved all performance aspects at small cache sizes. a b s t r a c tCloud-adopting enterprises have been increasingly employing multiple cloud providers concurrently, for example, to consume unique services and to mitigate data lock-in risk. As a consequence, the enterprises must be able to address contrasting quality-of-service degrees offered by the different providers. This paper presents an intelligent cloud cache eviction approach, namely i-Cloud, as the core component of a client-side cloud cache. i-Cloud is capable of reducing public cloud data-out expenses, improving cloud network scalability and lowering cloud service access latencies specifically in multi-provider cloud environments. Trace-driven simulations have shown that i-Cloud outperformed well-known approaches in all performance metrics. In addition, i-Cloud is not only able to achieve optimal performances in all metrics simultaneously but also delivered relatively stable performances across all performance metrics. The results have also indicated that taking the nonuniformity of data-out charge rates into cache eviction decisions improved caching performances in all metrics.

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“…The variety and veracity of Big Data and the performance, privacy and security concerns demand a comprehensive cloud solution with services from both private and public cloud offerings (Lee, Park, and Shin 2012). Banditwattanawong, Masdisornchote, and Uthayopas (2014) stored Big Data in hybrid clouds built with different public cloud providers for performance. Campa et al (2014) proposed an integrated programming framework for both local and remote resources for the offloading of computations from structured parallel applications to heterogeneous cloud resources.…”

Section: Hybrid Computing Infrastructure and Virtual Resource Burstingmentioning

confidence: 99%

Big Data and cloud computing: innovation opportunities and challenges

Yang

Huang

et al. 2016

International Journal of Digital Earth

645

289

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Big Data has emerged in the past few years as a new paradigm providing abundant data and opportunities to improve and/or enable research and decision-support applications with unprecedented value for digital earth applications including business, sciences and engineering. At the same time, Big Data presents challenges for digital earth to store, transport, process, mine and serve the data. Cloud computing provides fundamental support to address the challenges with shared computing resources including computing, storage, networking and analytical software; the application of these resources has fostered impressive Big Data advancements. This paper surveys the two frontiers-Big Data and cloud computingand reviews the advantages and consequences of utilizing cloud computing to tackling Big Data in the digital earth and relevant science domains. From the aspects of a general introduction, sources, challenges, technology status and research opportunities, the following observations are offered: (i) cloud computing and Big Data enable science discoveries and application developments; (ii) cloud computing provides major solutions for Big Data; (iii) Big Data, spatiotemporal thinking and various application domains drive the advancement of cloud computing and relevant technologies with new requirements; (iv) intrinsic spatiotemporal principles of Big Data and geospatial sciences provide the source for finding technical and theoretical solutions to optimize cloud computing and processing Big Data; (v) open availability of Big Data and processing capability pose social challenges of geospatial significance and (vi) a weave of innovations is transforming Big Data into geospatial research, engineering and business values. This review introduces future innovations and a research agenda for cloud computing supporting the transformation of the volume, velocity, variety and veracity into values of Big Data for local to global digital earth science and applications.

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Economical and efficient big data sharing with i-Cloud

Cited by 7 publications

References 9 publications

Knowledge and attitudes among life scientists towards reproducibility within journal articles: a research survey

Knowledge and attitudes among life scientists towards reproducibility within journal articles: a research survey

Multi-provider cloud computing network infrastructure optimization

Big Data and cloud computing: innovation opportunities and challenges

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